Chorological abductive inferring: case studies of tracing spatial dissemination of COVID-19

Abstract

Abstract COVID-19 did not disappear in the third year (2022) of the global pandemic. On the contrary, the number of infected people several times exceeded the highs of previous years, but the greater morbidity was not accompanied by a relatively comparable number of deaths. Some studies showed that the SARS-CoV-2 virus impact, e.g. in CEE EU countries, characterizes the seasonal intensity as temperatures fall or rise in relative humidity. All researchers agree that the number of COVID-19-infected people is only an estimate based on the volume of tests performed and that the true numbers are usually much higher. The implementation of spatial interaction modeling could potentially aid in the control of the COVID-19 pandemic due to the inherently spatial nature of its diffusion. The gravity models used in this investigation to simulate the regional spread of the COVID-19 epidemic are based methodologically on previous empirical studies. The proposed methodology uses techniques for modeling spatial interactions due to the epidemics described above, which are a direct result of the number of contacts between individuals. The COVID-19 pandemic can be studied regionally using spatial diffusion methods as well as population potential models (spatial interaction models) and visualized using geographic information system software. Empirical verification and geovisualizations are based on available recent population and pandemic statistics that are possible to acquire from national health services. Methodologically, this type of modeling and simulation aimed at reconstructing a factual situation can be defined as abductive chorological inferring.